This article is based on findings from Packt’s third annual Skill Up survey (2017), originally reported by JAXenter. The survey gathered responses from approximately 5,000 developers and tech professionals worldwide.
Survey Background: Skill Up 2017 at a Glance
Packt’s annual Skill Up survey aims to help developers and technical professionals stay current by tracking which tools, technologies, and trends are gaining traction across the industry. The 2017 edition gathered input from approximately 5,000 respondents worldwide, covering topics from tooling preferences to salary benchmarks and career development.
In 2016, respondents identified Virtual & Augmented Reality, Machine Learning, and the Internet of Things as the biggest upcoming trends. By 2017, the picture had shifted: Machine Learning, Big Data, and Cloud Computing moved to the top of the list. Cloud Computing was particularly championed by Full-Stack Developers and Systems Administrators.
Salary Landscape: Who Earns the Most in Tech?
The survey shed light on compensation across different technical roles. Some results were predictable; others were more surprising.
Top Five Earners
- C-Suite Level Managers
- Big Data Engineers
- Mid-Level Leads / Managers
- Security Engineers
- Information Architects
Cloud Engineers and DevOps Engineers ranked 6th and 7th respectively — above the industry average, but not at the very top. For a field that demands broad expertise across infrastructure, automation, and software delivery, the relatively high but not top-tier compensation for DevOps Engineers reflects how competitive and in-demand these skills have become.
Lowest-Paid Roles
- Hobbyists
- Game Developers
- Web Developers
- Technical Support
- Mobile Developers
It is notable that Game Developers and Mobile Developers — roles often perceived as glamorous or cutting-edge — appear near the bottom of the earnings table. This likely reflects highly saturated job markets and a large proportion of independent or freelance workers in those categories.
Skills That Command the Highest Salaries
When respondents were asked which specific technical skills were associated with the highest-paying roles, the results highlighted a mix of data engineering, operations tooling, and analytics platforms. The top five skills linked to the best compensation were:
- Splunk
- Hadoop
- Kafka
- Chef
- SAS
For DevOps practitioners, it is encouraging to see Hadoop and Chef in the top five. Hadoop signals the growing overlap between DevOps and Big Data engineering, while Chef’s presence confirms that configuration management expertise remains financially rewarding. Splunk’s top ranking reflects strong enterprise demand for log management and operational intelligence skills.
Most Popular Tools Across the Industry
Across all respondents, the three most widely used tools in 2017 were Python, Git, and Visual Studio. However, tool preferences diverged significantly by role:
- DevOps Engineers: Favored Docker over Visual Studio, using Python and Git alongside it.
- Cloud Engineers: Cited Python, Docker, and AWS as their primary tools.
- Information Architects: Preferred Python, Eclipse, and Visual Studio.
Docker’s prominence across both DevOps and Cloud Engineering roles underscores how container technology had already become a foundational part of modern infrastructure workflows by 2017.
The Top Tools to Learn Next: Docker, Ansible, and Kubernetes
When respondents were asked which tools they planned to learn over the next 12 months, the findings provided a clear signal for where DevOps careers were heading.
Across all respondents, the top three tools to learn were:
- Docker
- Python
- Angular
For DevOps Engineers specifically, the priorities were even more focused on container and automation tooling:
- Docker — Container runtime and image management
- Ansible — Agentless configuration management and automation
- Kubernetes — Container orchestration at scale
Cloud Engineers showed closely aligned priorities, but swapped Docker for OpenStack as their primary focus — reflecting a stronger emphasis on private and hybrid cloud infrastructure provisioning. Information Architects prioritized Docker, Hadoop, and React.
Why Docker, Ansible, and Kubernetes Still Matter
Although this survey data comes from 2017, the three tools DevOps engineers identified as critical learning priorities have only grown in importance since then. Understanding why professionals prioritized them helps explain the direction of modern infrastructure engineering:
Docker
Docker standardizes how applications are packaged and run by isolating them in lightweight containers. It removes environment inconsistencies between development, testing, and production — one of the most persistent pain points in software delivery. Its consistent image format also made it the natural starting point for any container-based workflow.
Ansible
Ansible’s agentless architecture and human-readable YAML playbooks made it one of the most accessible configuration management and automation tools available. It integrates well with cloud providers, container runtimes, and CI/CD pipelines, making it a practical choice for teams of any size.
Kubernetes
Kubernetes (K8s) addresses the challenge of running containers at scale — scheduling workloads, managing service discovery, handling rolling deployments, and maintaining desired system state. Its growing adoption by major cloud providers (Google GKE, AWS EKS, Azure AKS) confirmed its position as the de facto container orchestration standard.
Key Takeaways for DevOps Professionals
- Machine Learning, Big Data, and Cloud Computing were identified as the dominant industry trends in 2017, reflecting where engineering investment and hiring demand were concentrating.
- DevOps and Cloud Engineers rank among the higher-earning technical roles, though not at the very top of the pay scale.
- Configuration management (Chef, Ansible) and data platform skills (Hadoop, Kafka, Splunk) were most strongly associated with higher compensation.
- Docker, Ansible, and Kubernetes form a coherent, complementary skill set: containerization, automation, and orchestration — the three pillars of modern cloud-native infrastructure.
- Python remains a universal skill valued across DevOps, Cloud, and development roles alike.
Source: Packt Skill Up 2017 Survey, as reported by JAXenter.